2025.08. 24 本文字数：2293，阅读时长大约4分钟 作者 | 第一财经 齐琦 反内卷浪潮下，光伏、锂电池行业产能出清会议频开，引发市场高度关注。 "当前光伏、锂电池等板块的估值修复仅完成初期阶段，未来随着产能利用率提升，行情或将逐步见 顶。" 富国基金量化投资部ETF投资总监王乐乐于8月23日在2025雪球指数基金领袖峰会上分析 称，而农业、化工、建材等曾同样受困于"低价竞争"的传统行业，正通过差异化突围、产业链重构 与需求升级，成为"反内卷"背景下更具确定性的结构性机会所在。 近期A股市场"反内卷"题材轮动仍在继续，除了光伏、锂电，化工、农业等板块的资金关注度也快速 抬升。截至8月24日，化工50ETF、建材ETF、煤炭ETF、农业ETF，自七月以来累计涨幅分别为 16%、15%、10%、8%。 华创证券研究所副所长张瑜也在分析报告中提到，钢铁、水泥、光伏设备、能源金属等反内卷主题板 块近期表现强劲，多数跑赢大盘。政策面上，要求盘活存量、做优增量，通过优化竞争秩序推动传统 产业升级与新质生产力创新。而反内卷并非短期主题，背后是行业盈利改善与竞争生态优化的中长期 逻辑。 锂电、光伏"退烧"，产能出 ...

反内卷行情进入第二阶段 反内卷浪潮下，光伏、锂电池行业产能出清会议频开，引发市场高度关注。 "当前光伏、锂电池等板块的估值修复仅完成初期阶段，未来随着产能利用率提升，行情或将逐步见 顶。" 富国基金量化投资部ETF投资总监王乐乐于8月23日在2025雪球指数基金领袖峰会上分析称，而农 业、化工、建材等曾同样受困于"低价竞争"的传统行业，正通过差异化突围、产业链重构与需求升级， 成为"反内卷"背景下更具确定性的结构性机会所在。 近期A股市场"反内卷"题材轮动仍在继续，除了光伏、锂电，化工、农业等板块的资金关注度也快速抬 升。截至8月24日，化工50ETF、建材ETF、煤炭ETF、农业ETF，自七月以来累计涨幅分别为16%、 15%、10%、8%。 华创证券研究所副所长张瑜也在分析报告中提到，钢铁、水泥、光伏设备、能源金属等反内卷主题板块 近期表现强劲，多数跑赢大盘。政策面上，要求盘活存量、做优增量，通过优化竞争秩序推动传统产业 升级与新质生产力创新。而反内卷并非短期主题，背后是行业盈利改善与竞争生态优化的中长期逻辑。 机构看好化工、农业板块结构性机会 "内卷的本质是低效竞争导致的增收不增利陷阱企业陷入增产、降价 ...

Core Viewpoint - The construction materials sector is experiencing significant capital inflow, with over 90 million units net inflow into the construction materials ETF (159745), indicating strong investor interest in construction assets [1] Demand Side Analysis - Important national meetings, such as the Two Sessions and the Central Political Bureau meeting, have focused on stabilizing the real estate market, which is expected to boost demand for construction materials [1] - The Central Urban Work Conference emphasized urban renewal, which includes the renovation of urban villages and old housing, as well as upgrading old pipelines, likely increasing demand for pipes, waterproofing materials, and coatings [1] - Future policy support for home decoration, old renovations, and urban renewal is anticipated, which may enhance confidence in the industry chain [1] Supply Side Analysis - The trend of "anti-involution" is expected to lead to positive changes in the supply side of industries such as coatings, waterproofing, and cement, gradually optimizing the industry structure [1] - There is potential for recovery in profit margins for companies within the construction materials sector as supply conditions improve [1] Industry Outlook - With demand recovering and supply optimizing, the construction materials industry is poised for a turnaround, with 2025 projected to be a year of profit recovery for the sector [1] - Continued improvement in demand could provide greater recovery potential for the industry [1] Investment Opportunities - Investors are encouraged to seize opportunities arising from the sector's turnaround and marginal improvement in fundamentals [1] - The construction materials ETF (159745) tracks the CSI All Share Construction Materials Index, which includes segments such as cement, glass, and consumer construction materials [1] - Investors without stock accounts can consider the linked fund (013020) to access investment opportunities in the construction materials sector [1]

Core Viewpoint - The article discusses the recent adjustments made by commodity exchanges to cool down the market, specifically focusing on the increased transaction fees for glass, soda ash, and caustic soda futures, which have led to a notable decrease in trading volume and market activity [1][2]. Group 1: Fee Adjustments - The Zhengzhou Commodity Exchange announced an increase in transaction fees for various futures contracts effective from July 30, 2025, including a fee of 10 yuan per hand for glass futures and a fee of 0.04% of the transaction amount for soda ash futures [2]. - The transaction fee for caustic soda futures was set at 0.02% of the transaction amount for both regular and intraday positions [2]. Group 2: Market Reactions - Following the fee adjustments, there was a significant rebound in previously declining futures, with coking coal rising over 6%, glass increasing by over 4%, and both coking coal and soda ash seeing gains of over 3% [3]. - Despite the rebound, the overall trading volume in the futures market dropped significantly, with a 31.89% decrease to 38.76 million contracts and a 23.45% decrease in transaction value to 32.13 billion yuan, marking the lowest levels since July 21 [4]. Group 3: Capital Flow and Positioning - The glass and soda ash markets continued to experience capital outflows, with glass seeing a net outflow of 221 million yuan and soda ash 102 million yuan [4]. - Open interest in both glass and soda ash futures has been declining, with glass positions down by 26,700 contracts and soda ash by 41,500 contracts [4]. Group 4: Market Dynamics - The black series commodities showed mixed performance, with coking coal continuing to decline but at a reduced rate, while rebar and hot-rolled coil saw approximately 2% increases [6]. - The rebar futures contract closed at 3,347 yuan per ton, with a 1.98% increase and significant capital inflow, indicating a shift in investor focus towards rebar and hot-rolled coil [7].

Core Viewpoint - The current market is in a bull phase, with significant losses reported among short sellers in commodity and stock index futures. The article suggests that the most certain investment opportunities in a bull market are either in leading sectors or in severely undervalued stocks [2]. Group 1: Investment Opportunities - The article emphasizes that low-priced stocks tend to be driven up to reasonable levels during a bull market, indicating that underperforming sectors may see substantial gains due to ongoing liquidity and policy support [2]. - The upcoming major meetings are expected to enhance expectations for "stabilizing growth," which may provide considerable policy space for undervalued industries [2]. Group 2: ETF Analysis - The article utilizes the net value percentile calculation method to assess which sectors are currently in a state of severe undervaluation [3]. - A table is provided showing various ETFs, their net value percentiles since 2023 and 2024, and their performance in 2025, highlighting sectors like photovoltaic, alcohol, and real estate [7]. Group 3: Sector-Specific Insights - The photovoltaic sector is identified as particularly undervalued, with ETFs like the photovoltaic ETF (515790.SH) and new energy ETF (516160.SH) showing significant declines. The sector's performance is closely tied to government policies aimed at stabilizing growth [9][10]. - The alcohol sector, particularly the alcohol ETF (512690.SH), is also noted for being in a state of decline, with a lack of clear catalysts for recovery until consumer data improves [20][21]. - The real estate sector shows signs of divergence, with the real estate ETF (159707.SZ) experiencing intermittent policy-driven rallies but ultimately returning to lower levels [25][26]. Group 4: Medical and Pharmaceutical Sector - The medical and pharmaceutical sectors are highlighted as being collectively undervalued, with various ETFs like the biopharmaceutical ETF (159859.SZ) showing potential for recovery due to recent policy shifts regarding procurement practices [33][35]. - The medical ETF (512170.SH) is also mentioned as being in a relatively low valuation position, with a modest performance outlook [39]. Group 5: Commodity and Chemical Sectors - The coal sector has seen a significant price drop but is experiencing a rebound due to rising prices in coking coal and coke futures, with the coal ETF (515220.SH) reflecting this trend [43][45]. - The chemical sector is noted for its broad product range and recent price increases in lithium carbonate, with the chemical ETF (159870.SZ) positioned as relatively undervalued [49][54]. Conclusion - The article concludes that sectors such as chemicals, biopharmaceuticals, medical, alcohol, and photovoltaic are currently in a state of severe undervaluation, presenting potential investment opportunities for discerning investors [56].

- Model Name: Diffusion Index Model; Construction Idea: The model is based on the principle of price momentum, capturing industry trends through diffusion indices; Construction Process: The model tracks the weekly and monthly changes in the diffusion indices of various industries, ranking them accordingly. The formula for the diffusion index is not explicitly provided; Evaluation: The model has shown varying performance over the years, with significant drawdowns during market reversals[24][25][28] - Model Name: GRU Factor Model; Construction Idea: The model utilizes GRU (Gated Recurrent Unit) deep learning networks to process minute-level volume and price data, aiming to capture trading information; Construction Process: The model ranks industries based on GRU factors, which are derived from the deep learning network's analysis of trading data. The specific formula for GRU factors is not provided; Evaluation: The model has performed well in short cycles but has shown general performance in longer cycles[31][32][35] - Diffusion Index Model, Average Weekly Return: 0.89%, Excess Return Since July: -3.47%, Excess Return YTD: -0.45%[28] - GRU Factor Model, Average Weekly Return: 4.27%, Excess Return Since July: 1.34%, Excess Return YTD: -4.25%[35] - Factor Name: Diffusion Index; Construction Idea: The factor is based on the momentum of industry prices, capturing upward trends; Construction Process: The factor is calculated by observing the weekly and monthly changes in the diffusion indices of various industries. The specific formula is not provided; Evaluation: The factor has shown varying performance, with significant drawdowns during market reversals[24][25][28] - Factor Name: GRU Factor; Construction Idea: The factor is derived from GRU deep learning networks, capturing trading information from minute-level volume and price data; Construction Process: The factor is calculated by ranking industries based on the GRU network's analysis of trading data. The specific formula is not provided; Evaluation: The factor has performed well in short cycles but has shown general performance in longer cycles[31][32][35] - Diffusion Index Factor, Top Industries: Comprehensive Finance (1.0), Steel (1.0), Non-Bank Finance (0.999), Comprehensive (0.998), Non-Ferrous Metals (0.997), Home Appliances (0.995)[25] - GRU Factor, Top Industries: Banking (3.3), Real Estate (0.58), Oil & Petrochemicals (-1.26), Textile & Apparel (-1.73), Light Manufacturing (-2.49), Electric Power & Utilities (-2.83)[32]

Market Performance - The A-share market saw all three major indices rise, with the Shanghai Composite Index increasing by 1.67%, the Shenzhen Component Index by 2.33%, and the ChiNext Index by 2.76% [1] - The Sci-Tech 50 Index led the market with a weekly increase of 4.63%, driven by technology stocks such as semiconductors and AI [1] ETF Market Trends - The ETF market displayed a pattern of "debt fund hedging + Hong Kong stock technology attracting capital," with a total net inflow of 18.18 billion yuan [4] - Rare metals and rare earth-related ETFs continued to perform well, with coal and building materials ETFs rising nearly 10% as part of a "anti-involution" trend [1] - In contrast, several bank-related ETFs experienced a decline of around 3% [1] Fund Flows - Stock ETFs saw a net outflow of 54.5 billion yuan, while industry ETFs recorded a net inflow of 116.59 billion yuan [4] - Cross-border ETFs had a net inflow of 102.55 billion yuan, benefiting from the recent capital inflow into the Hong Kong market [4] - Bond ETFs experienced a net inflow of 91.82 billion yuan [4] Upcoming ETF Issuances - Six new ETFs are set to be issued next week, including Hong Kong Stock Connect Consumer ETF and Hong Kong Stock Connect Technology ETF [4]

Quantitative Models and Construction Methods 1. Model Name: Genetic Programming Industry Rotation Model - **Model Construction Idea**: This model directly extracts factors from industry indices' price-volume and valuation data, updating the factor library at the end of each quarter. It selects the top five industries with the highest multi-factor composite scores for equal-weight allocation on a weekly basis[3][32] - **Model Construction Process**: - Factor extraction is performed on industry indices based on price-volume and valuation data - The factor library is updated quarterly - Weekly rebalancing is conducted, selecting the top five industries with the highest composite scores for equal-weight allocation[3][32] - **Model Evaluation**: The model achieved strong absolute and relative returns but exhibited rapid industry rotation, leading to slight underperformance against the benchmark in the previous week[3][32] 2. Model Name: Absolute Return ETF Simulated Portfolio - **Model Construction Idea**: Asset allocation weights are determined based on recent trends, with stronger-trending assets assigned higher weights. Equity allocation within the portfolio follows the monthly views of an industry rotation model[4][37] - **Model Construction Process**: - Asset classes are weighted based on recent trend strength - Equity allocation is determined by a monthly industry rotation model - The portfolio includes equity ETFs (e.g., dividend, healthcare, metals) and commodity ETFs (e.g., energy, soybean meal)[4][39] - **Model Evaluation**: The portfolio demonstrated stable performance with a focus on trend-following and diversification[4][37] --- Model Backtesting Results 1. Genetic Programming Industry Rotation Model - **Annualized Return**: 31.87% - **Annualized Volatility**: 18.18% - **Sharpe Ratio**: 1.75 - **Maximum Drawdown**: -19.63% - **Calmar Ratio**: 1.62 - **Year-to-Date (YTD) Return**: 28.68% - **Weekly Performance**: 3.03%[35] 2. Absolute Return ETF Simulated Portfolio - **Annualized Return**: 6.53% - **Annualized Volatility**: 3.82% - **Maximum Drawdown**: -4.65% - **Sharpe Ratio**: 1.71 - **Calmar Ratio**: 1.41 - **Year-to-Date (YTD) Return**: 5.58% - **Weekly Performance**: 0.33%[38] --- Quantitative Factors and Construction Methods 1. Factor Name: Market Intrinsic Momentum Indicators - **Factor Construction Idea**: These indicators measure the internal momentum of the market by analyzing the distribution of individual stock performance[18][19] - **Factor Construction Process**: - **Indicator 1**: Daily turnover difference between rising and falling stocks, normalized by total turnover $ \text{Indicator 1} = \frac{\text{Turnover of rising stocks - Turnover of falling stocks}}{\text{Total turnover}} $ - **Indicator 2**: Monthly high-low turnover difference, normalized by total turnover $ \text{Indicator 2} = \frac{\text{Turnover of stocks hitting monthly highs - Turnover of stocks hitting monthly lows}}{\text{Total turnover}} $ - **Indicator 3**: Six-month high-low turnover difference, normalized by total turnover $ \text{Indicator 3} = \frac{\text{Turnover of stocks hitting six-month highs - Turnover of stocks hitting six-month lows}}{\text{Total turnover}} $ - **Indicator 4**: Annual high-low turnover difference, normalized by total turnover $ \text{Indicator 4} = \frac{\text{Turnover of stocks hitting annual highs - Turnover of stocks hitting annual lows}}{\text{Total turnover}} $[18][19] - **Factor Evaluation**: These indicators effectively capture short-term and long-term market strength and provide strong signals for market trends[19] --- Factor Backtesting Results 1. Market Intrinsic Momentum Indicators - All four indicators showed upward trends in recent periods, aligning with the market's upward trajectory, indicating strong internal momentum supporting the index's rise[19]

Group 1 - The Yarlung Tsangpo River downstream hydropower project has officially commenced with a total investment of 1.2 trillion yuan, planning to build five hydropower stations, with an annual power generation capacity equivalent to three times that of the Three Gorges Dam, which is expected to stimulate related theme ETFs [1] Group 2 - Various ETFs including construction materials ETF, infrastructure 50 ETF, and chemical ETF have seen increases this week, with over 1 billion yuan net inflow into 43 funds, including steel ETF and construction materials ETF, which have net inflows of 14.24 billion yuan and 11.05 billion yuan respectively [2] - The construction materials ETF tracks the CSI All Share Construction Materials Index, covering sectors such as cement (44.8%), decoration materials (35.3%), and glass fiber (10%), with key stocks benefiting from the Yarlung Tsangpo River project [2] - The infrastructure ETF tracks the CSI Infrastructure Index, encompassing the infrastructure and engineering machinery industry chain [3] - The steel ETF tracks the CSI Steel Index, covering iron ore mining, steel smelting, and processing, aiming to reflect the overall performance of steel-related companies in the A-share market [4] - The chemical ETF tracks the CSI Subdivided Chemical Industry Theme Index, covering various chemical sectors, with leading stocks including Wanhua Chemical and Salt Lake Shares [4] Group 3 - The "anti-involution" policy is expected to optimize the industry landscape, with leading companies likely to see a turning point in profitability, particularly in sectors like steel, glass fiber, and new energy chains, which are currently at historical lows in profitability and capital expenditure [5] - The market is experiencing significant activity with daily trading volume reaching nearly 1.9 trillion yuan, driven by liquidity and policy deployment, with optimistic expectations being rapidly priced in [6] - The main market themes currently revolve around "anti-involution" and large infrastructure projects, with opportunities identified in power equipment, resource products, and construction materials sectors [6] - The "anti-involution" policy is anticipated to bring positive changes to the industry chain, potentially reshaping competitive dynamics and leading to price recovery in some high-end manufacturing sectors [7]

- The report does not contain any specific quantitative models or factors for analysis[1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39]